Description
This indicator measures the level of financial inclusion in a country as measured by the number of bank branches and ATMs per 100,000 adults and the share of adults that have a financial or mobile money account.
Relationship to Growth & Poverty Reduction
The ability to access affordable credit is a critical element of private sector led growth, particularly for small businesses that often lack the initial capital needed to grow and expand and also for agricultural households, where expenditures on inputs precede the returns from harvest; it also increases a business or household’s ability to bear and cope with risk.68 Financial inclusion and access to both formal and informal financial instruments are crucial for rural and poor populations to be able to manage uncertain and uneven incomes and alleviate the costs of poverty while promoting inclusive growth.69 Improving credit access for small business and poor populations can have a substantial impact on agricultural development, poverty reduction, and broad-based economic growth.70
Methodology
Indicator Institution Methodology
The Access to Credit composite indicator is calculated by taking the simple average of two indicators from the IMF and Findex, which have been normalized and ranked on equivalent scales:
- Financial Institution Access (IMF): MCC uses the Financial Institution Access indicator from the IMF’s Financial Development Index. This indicator has two sub indicators: the number of bank branches per 100,000 adults from the World Bank’s FinStats, and the number of ATMs per 100,000 adults from the IMF’s Financial Access Surveys.
- Share of adults with an account (Findex): From the World Bank’s Findex Database, MCC uses the share of the population (adults 15+) with an account. This survey counts both accounts with traditional financial institutions and mobile money.
MCC’s Access to Credit Score = [ 0.5 x Normalized IMF] + [ 0.5 x (Normalized Findex)]
This index draws on 2020 data from the Findex database (as well as 2021 data for those countries added to the dataset in the March 2023 update) and 2021 data published in 2023 by the IMF. Country scores are reported on the Scorecards as 2022 data. When one indicator is missing data, the other is used. Since each of the two sub-components of this index have different scales, MCC created a common scale for each of the indicators by normalizing them. Please see equations below. Both scales are then inverted so that a higher score corresponds to better performance.
MCC Methodology to Normalize IMF and Findex Data:
- Normalized IMF = (Number of countries scoring below Country X on IMF’s raw data in the income group) ÷ (Number of Countries scoring equal to or greater than Country X on IMF’s raw data in the income group + Number of countries scoring below Country X on IMF’s raw data in the income group)
- Normalized Findex = (Number of countries scoring below Country X on Findex raw data in the income group) ÷ (Number of Countries scoring equal to or greater than Country X on Findex’s raw data in the income group + Number of countries scoring below Country X on Findex’s raw data in the income group)
For example, to calculate a give country X’s score, MCC first finds the number of countries that score worse than that country in the income pool, and the number of countries that have the same or better score than country X on the sub-source. MCC then divides the number of countries below by the sum of the number of countries below and the number of countries equal or above. Missing values are not included in these calculations. Finally, MCC averages the normalized values for each source together. If IMF or Findex are missing, the normalized score for the other is used, but if both are missing the indicator is considered missing and assigned an “N/A”.
In FY25 MCC revised its methodology for this indicator to address issues of missing data. As a result, the scores from FY25 are not comparable to scores from FY24 and earlier.
Source
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Financial Development Index (IMF)
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World Bank Findex Database (Findex)